Fit logistic regression

In this exercise, you will continue with the data from the study on the contamination of ground water with arsenic in Bangladesh where you want to model the probability of switching the current well given the level of arsenic present in the well.

Recall the dataset structure:

Dataset wells is preloaded in the workspace.

This exercise is part of the course

Generalized Linear Models in Python

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Exercise instructions

Import statsmodels and glm.
Using glm() fit a logistic regression model where switch is predicted by arsenic.
Print model summary using .summary().

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Load libraries and functions
import ____.api as sm
from ____.____.api import glm

# Fit logistic regression model
model_GLM = ____(formula = ____,
                data = ____,
                family = ____.____.____).____ 

# Print model summary
print(____.____)

Edit and Run Code